Short Duration Rainfall Extremes in Ireland: Influence of Climatic Variability

A widely-noted change in the North Atlantic circulation in the 1970s affected the spatial distribution and seasonal pattern of rainfall over Ireland. To examine if this was accompanied by a change on short duration precipitation extremes, multi-decadal time series from the second half of the twentieth century of thirteen hourly precipitation stations in Ireland have been analysed for the occurrence of extreme values over several durations of up to 24 h. Strong evidence was found for a change since the late 1970s in short duration rainfall depths, particularly in the west of the country. Precipitation depth-duration-frequency analyses over two sub-periods showed that at several locations, storm event magnitudes which corresponded to a 30 year return period before 1975 had a return period close to 10 years in the post-1975 period. The widespread increase in spring and autumn rainfall and the local increases in the frequencies and magnitudes of severe rainfalls have implications for engineering hydrology, flood risk analysis and water resources management. The necessity of using up-to-date data to derive design storm magnitudes is stressed, due to the possible influence of underlying climatic shifts. Furthermore, as non-stationarity has been demonstrated, the use of long timeseries extending beyond thirty years into the past will result in underestimation of storm intensities in many areas.     

Validation of MSWEP daily and extreme precipitation of the Taihu Lake Basin in Jiangsu ProvinceEI北大核心CSCD

基于1979—2019年江苏省太湖流域雨量站实测降水资料,综合解析了全球性降水资料MSWEP(multi-source weighted-ensemble precipitation)对日降水量和各历时极值降水量的表征能力。结果表明:MSWEP对研究区日降水量总体上有较强的解释能力,但在山丘区较集中的湖西区和以水域为主的太湖区两个水利分区的精度相对较差,同时MSWEP难以捕捉到暴雨等级的日降水事件;MSWEP可大致反映研究区各历时极值降水量的空间分布格局,但在细节特征上与地面降水场仍有一定差异;随着历时增加,MSWEP极值降水量的精度不断提高,MSWEP对15 d及更长历时极值降水量具有较强的定量表征能力;MSWEP日降水量和极值降水量的误差与降水强度之间均有显著的线性负相关性,存在较明显的“低值高估、高值低估”现象,且MSWEP的精度与空间尺度有关;在研究区面平均尺度上,由于降水量的空间均化效应和尺度不匹配性的消除,MSWEP对日降水量和极值降水量的表征能力明显优于栅格尺度。     

镇江市降雨场次划分与暴雨特性分析

为划分镇江市降雨场次和分析暴雨特性,基于丹徒站1981-2016年汛期5-10月的逐分钟降雨资料,确定了降雨间隔时间,筛选了暴雨场次,分析了汛期各月暴雨次数和暴雨量的变化特性,解析了不同历时和不同强度暴雨的演变规律.结果表明:镇江市合理的降雨间隔时间为2 h;汛期总暴雨次数呈略微上升的趋势,总暴雨量以每10年43.4 ...     

深圳市1953-2012年极端气候事件变化分析

全球气候变化导致极端气候事件频发,选择描述极端气候事件的相关指标,利用Mann-Kendall趋势检验法等对深圳市1953-2012年极端气候指标进行分析。结果表明:总体上深圳市降水频次与极端降水量均呈现起伏不定的变化规律,四季极端降水量主要集中在夏季,全年和四季降水量均没有明显的变化趋势。深圳市极端气温总体呈现较为显著稳定的变化状况;极端高温事件不断增加,极端低温事件不断减少,且趋势显著,同一季节的气温差异性较大,且差异性呈现出比较显著的加大趋势。     

Regionalization of Rainfall Intensity-Duration-Frequency using a Simple Scaling Model

Design storm is one of the most important tools to design hydraulic structures, hydrologic system and watershed management, mostly extracted by intensity- duration - frequency (IDF) curves for a given specific duration and return period. As for conventional methods to calculate IDF curves, the precipitation should be recorded for different durations so that foregoing curves can be extracted. Such data can be collected from rain gauge stations. In many areas, just daily precipitation data are available by which IDF curves cannot be extracted as per conventional methods. The aim of this research is to make IDF curves for short-term durations according to time scaling model as well as daily rainfalls. The relationships of this method are characterized with three variables including mean (μ ₂₄) and standard deviation (σ ₂₄) of daily rainfall intensity, and scaling exponent (H) by which all IDF curves might be drawn. The method used in present paper entails for less computational steps than conventional methods and by far has low parameters considerably than others in turn increases reliability. Scaling method is used to extract the IDF curves in rain-gauge stations in Khuzestan province located in southwest Iran and results proved the efficiency and robustness of the scaling method. Also ability of scaling concept method was examined in constructing of regional IDF.     

The Spatiotemporal Characteristics of Extreme Precipitation Events in the Western United States

Changes in the frequency or intensity of extreme precipitation events would have profound impacts on both human society and the natural environment. In this paper, we present the results of a comprehensive analysis of the spatiotemporal changes of extreme precipitation in the western United States. The analyses explore the spatial characterization of the El Nino-Southern Oscillation (ENSO)-extreme precipitation response pattern and identify the multi-scale temporal variability in precipitation extremes in the western United States. Results indicate: (1) Extreme precipitation expressed in indices such as seasonal count of days when precipitation is large than 10 mm (R10), seasonal maximum 5-day precipitation (R5D), maximum length of dry spell (CDD), and seasonal total precipitation exceeding 95 percentile (R95) have a dipolar pattern and a transition zone which separates the west into two main dipolar centers regarded as Pacific Northwest and Desert Southwest. The simple precipitation intensity index (SDII) has little correlation with large scale natural oscillations over most of the west. (2) The spatial distributions of annual trend of R10, R5D, SDII, and R95 have seasonal variability in southern California and Lower Colorado River Basin. (3) There are consistent multi-year bands ranging from 2 to 20 years in the R10, R5D, CDD, and R95 winter time series which may be caused by the inter-decadal or multi-decadal modulation of ENSO effects on precipitation extremes. The results can provide beneficial reference to the prediction of precipitation extremes in the west.

     

21st Century Drought Scenarios for the UK

A 6-month drought severity index (DSI6) is applied to each of the 11-member perturbed-physics ensemble (HadRM3-PPE-UK) monthly precipitation dataset from 1950 to 2100 to investigate projected 21st century droughts in the UK. Four main drought characteristics are investigated: intensity, drought covariance, frequency of drought months and frequency of drought events at a given duration. Changes in these characteristics are analysed for 30-year periods: 1970–1999 (1980s), 2010–2039 (2020s), 2040–2069 (2050s) and 2070–2099 (2080s) and described in terms of their seasonal behaviour, for both moderate and extreme droughts. Projections of drought characteristics are expressed in the forms of ensemble-mean change relative to the 1980s and model consensus, and analysed over 23 water resource regions. In general, drought characteristics show profound increases (and widespread) for the 2050s and 2080s with larger change occurring during the wet season and under moderate drought conditions. Drought covariance sees greater increase during the dry season with greater change magnitude (but less widespread) under extreme drought conditions. Results also show that droughts can persist over long durations. However, the projected frequency of droughts at longer durations is low compared with droughts with shorter duration of persistence. Water resource regions (WWRs) mostly show negative change in drought characteristics, except for drought covariance. However, intensity and duration of droughts also generally increase over most of the WRRs in England, which are already highly exploited. Of particular relevance to water management, results from this ensemble have a strong influence on dry season water availability, especially in parts of England.     

Influence of Trend on Short Duration Design Storms

Design storms (DS) that are determined from intensity-duration-frequency (IDF) relationships are required in many water resources engineering applications. Short duration DS are of particular importance in municipal applications. In this paper, linear trends were estimated for different combinations of durations and frequencies (return periods) of annual short-duration extreme rainfall. Numerical analysis was performed for 15 meteorological stations from the province of Ontario, Canada. The estimated magnitude (rate mm/h) and direction of trend (increasing, decreasing, or no trend) were estimated and then used to quantify the effect of trend on the frequency of design storms. Significant trends were detected for all durations. It was determined that due to the existence of trends (which might be attributed to climate change), the design storms of a given duration might occur more frequently in the future by approximately as much as 36 years depending on the duration and return period.     

海河流域1961-2010年极端气温与降水变化趋势分析

以海河流域30个气象基准站1956年－2010年气温和降水日值资料为基础,选取12个表征极端气候变化指标,分析了海河该流域极端气温与降水的变化趋势。结果表明：海河流域极端高温的强度、频度和持续时间均有较强的增加趋势,;极端低温的强度、频度显著降低,反映出流域整体增温的气候变化背景。;海河流域短历时极端降水强度有增大趋势,年极端降水的发生频次降低,连续湿日表现出一定的减少趋势,而连续干日在近几十年来有一定的增加趋势,区域呈现弱干化趋势。从年代际变化特征看,20世纪90年代以来,年极端高温事件和短历时强降水事件发生趋于频繁,而长持续性降水事件的降水量减少。海河流域整体的暖干趋势以及降水集中的趋势,将对农业生产、水资源开发利用造成不利影响;,同时,短历时极端强降水事件的增加可能加剧局地的山洪灾害和城市内涝的风险。     

1892-2010年间重庆主城降水变化趋势分析

 针对近年来普遍存在的城市雨洪灾害问题,利用重庆市沙坪坝气象站1892—2010年的逐月降水量资料,采用线性倾向估计和方差分析法（ANOVA）分析了119 a来重庆主城不同统计时段的降水量及不同等级的降水频率,探讨了近百年来重庆市主城区域降水变化的趋势,以期为城市雨洪灾害防治及城市排水规划的决策提供科学指导。结果表明：119 a来,全年及汛期降水量稍有增加的趋势,年降水量增长向汛期趋于集中;此外,近30 a来,主城区域降水量年际变化幅度有明显的扩大趋势,较大等级降水的发生频率也明显增加;特别是最近10 a,该变幅更加剧烈,连续时段内灾害性气候的发生频率有增长趋势,加剧了城市汛期排水系统的压力。     

近50年来西藏极端降水时空变化特征

利用1961~2010年西藏地区9个气象站点逐日降水资料,结合百分位方法定义的极端降水阈值,分析了该地区极端雨日及其平均降水强度、不同持续时间的极端降水事件、气候变化对极端降水的时空变化特征的影响。结果表明:(1)92°E以西的地区,极端雨日平均降水强度呈现出增加的趋势,而在92°E以东的地区,呈现出减小的趋势;(2)极端降水事件以持续1 d为主,其频率一般在4.3次/年以上,强度一般在20 mm/d以上,林芝站和波密站为频率和强度高值区;(3)气候变化背景下,极端降水的频率、强度表现出西移的态势。     

Uncertainties and trends in extreme rainfall series in Tuscany,Italy: Effects on urban drainage networks design

Sound basin management at urban or greater scale needs reliable design storm definition. A statistical analysis is carried out on extreme annual rainfall series for durations of 1, 3, 6 and 12 hours occurring at two gauges in Tuscany, Italy. Kendall's test is applied to the extremal series to detect a definite increasing (or decreasing) trend. A special form of an ARIMA model is also fitted to the series to quantify possible linear trends and their respective significance. Results show a clearly increasing trend at shortest duration at both gauges, no trend at longer ones. Time evolution of design storms for all durations and return periods up to 25 years is derived and analysed based on Gumbel distribution. Applications are presented concerning impacts of uncertainties for the design of urban drainage networks.     

Evaluating Future Joint Probability of Precipitation Extremes with a Copula-Based Assessing Approach in Climate Change

Changes in climate extremes may cause the variation of occurrence and intensity of floods and droughts. To investigate the future changes in joint probability behaviors of precipitation extremes for water resources management, an approach including three stages for analyzing the spatial variation of joint return periods of precipitation extremes is proposed in this paper. In the first stage, a weather generator model (WGM) was conducted with general circulation models (GCMs) under representative concentration pathway (RCP) scenarios to generate daily rainfall time series during 2021–2040 (S) and 2081–2100 (L) based on the statistics of the observed rainfall data. Four extreme precipitation indices are defined to represent extreme precipitation events. In the second stage, copula methods are adopted to establish the joint distribution of the precipitation extreme indices. The watershed-scale assessment of flood and drought applied in Shih-Men reservoir in northern Taiwan is conducted to demonstrate the possible change of joint return period. In the third stage, the change rates of joint return periods for bivariate extreme indices are demonstrated to present the occurrence possibility of floods or droughts in the future. The results indicate that floods and droughts might occur more frequently in the upstream region of the reservoir during the twenty-first century. The reservoir operations would be more important for water supply and flood mitigation. In conclusion, the possible changes of future joint probability of the precipitation extremes should be paid attention to for water resources management and draft plans to confront potential challenges in the future.     

The effect of climate change on urban drainage: an evaluation based on regional climate model simulation.

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 x 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at timescales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.     

Non-Stationary Rainfall Intensity-Duration-Frequency Relationship: a Comparison between Annual Maximum and Partial Duration Series

The rainfall Intensity-Duration-Frequency (IDF) relationship is the primary input for storm water management and other engineering design applications across the world and it is developed by fitting an appropriate theoretical probability distribution to annual maximum (AM) series or partial duration series (PDS) of rainfall. The existing IDF relationship developing methods consider the extreme rainfall series as a stationary series. There exist few studies that compared AM and PDS datasets for developing rainfall IDF relationship in a stationary condition. However, during the last few decades, the intensity and frequency of extreme rainfall events are increasing due to global climate change and creating a non-stationary component in the extreme rainfall series. Therefore, the rainfall IDF relationship developed with the stationary assumption is no longer tenable in a changing climate. Hence, it is inevitable to develop non-stationary rainfall IDF relationship and to understand the differences in non-stationary rainfall IDF relationships derived using AM and PDS datasets. Consequently, the objectives of this study are: (1) to develop non-stationary rainfall IDF relationships using both AM and PDS datasets; (2) to compare them in terms of return level estimation. In particular, the non-linear trend in different durations’ PDS and AM datasets of Hyderabad city (India) rainfall is modeled using Multi-objective Genetic Algorithm (MGA) generated Time based covariate. In this study, the PDS datasets are modeled by the Generalized Pareto Distribution (GPD) while the AM datasets are modeled by the Generalized Extreme Value Distribution (GEVD). The time-varying component is introduced in the scale parameter of the GPD and the location parameter of the GEVD by linking the MGA generated covariate. In addition, the complexity of each non-stationary model is identified using the corrected Akaike Information Criteria (AICc) and the statistical significance of trend parameter in the non-stationary models is estimated using the Likelihood Ratio (LR) test. Upon detecting significant superiority of non-stationary models, the return levels of extreme rainfall event for 2-, 5-, 10- and 25-year return periods are calculated using non-stationary models. From the results, it is observed that the non-stationary return levels estimated with PDS datasets are higher than those estimated with AM datasets for short durations and smaller return periods while the non-stationary return levels estimated with AM datasets are higher than those estimated with PDS datasets for long durations and higher return periods.     

昆明地区降水、气温及极端天气的长期变化趋势

利用昆明气象站1951年-2013年逐日气温和降水资料,采用线性趋势、Sen斜率估计、Mann-Kendall等方法分析昆明降水、气温和极端天气的变化特征与趋势,结果表明:1951年-2013年间,1994是年平均气温突变点;年平均气温和四季气温均呈升温趋势;年降水量和夏、秋两季降水量呈下降趋势,春、冬两季降水呈上升趋势,但趋势并不显著;在极端降水指数中,持续湿期呈下降趋势,持续干期和一日最大降水量呈上升趋势,趋势并不显著;在极端温度指数中,热日持续指数、暖夜指数及暖昼指数均呈显著上升趋势,冷日持续指数、冷夜指数及冷日指数均呈显著下降趋势。     

Heatwaves and storms contribute to degraded water quality conditions in the nearshore of Lake Ontario

As extreme climatic events, such as heatwaves and storms, become more frequent in response to changing climates, understanding the role climatic events play on water quality is essential. Here, we use water quality monitoring data collected from the nearshore of Lake Ontario between 2000 and 2018 to ask: i) which sites in the nearshore of Lake Ontario have statistically extreme water quality conditions?; ii) do water quality conditions differ in extreme versus non-extreme climate years?; and iii) what are the significant antecedent extreme weather drivers of water quality in the nearshore of Lake Ontario? Three sites with the highest chlorophyll a concentrations and eutrophic conditions, two of which are in Areas of Concern, exhibited the strongest responses to climate extremes. Antecedent weather conditions explained 87.2% of the variation in extreme chlorophyll a concentrations. In particular, warmer temperatures and heatwaves corresponded with statistical extremes in chlorophyll a concentrations. Precipitation accounted for 35.5% of the variation in extreme conditions of turbidity, including storm events the day prior to sampling. When considering site-specific extreme conditions, antecedent weather conditions explained 66.8% of the variation in turbidity. We illustrate the strong role that heatwaves and storm events play on spatial and temporal patterns in extreme water quality conditions, highlighting the importance of incorporating climate change adaptation plans into ecosystem management strategies to preserve water quality in the highly important and iconic nearshore regions of the Laurentian Great Lakes.     

大伙房水库汛期径流变化趋势及影响因素定量分离研究

基于大伙房水库1961—2004年汛期各月降雨径流资料,利用Mann-Kendall趋势检验法、Mann-Kendall突变检验法、Pettitt突变检验法和降雨—径流深双累积曲线方法,分析了大伙房水库汛期降雨、汛期径流深、最大月降雨和最大月径流深四类序列的趋势和跳跃特性,并利用累积量斜率变化率定量评价了降雨和人类活动对汛期径流深和最大月径流深的影响。结果表明:(1)流域汛期降雨和径流深下降趋势不显著,最大月降雨和最大月径流深上升趋势不显著;(2)汛期降雨、径流深、最大月降雨和最大月径流深突变不显著,降雨径流关系变异年份分别为1975、1985和1995年,1975年后流域汛期产流能力减弱;(3)大伙房水库汛期径流变化经历了4个阶段,人类活动是导致水库汛期径流深减少的主要原因,降雨变化是导致最大月径流深增加的主要原因。     

Assessment of Extreme Precipitation in Future through Time-Invariant and Time-Varying Downscaling Approaches

Skill of a time-varying downscaling approach, namely Time-Varying Downscaling Model (TVDM), against time-invariant Statistical Downscaling Model (SDSM) approach for the assessment of precipitation extremes in the future is explored. The downscaled precipitation is also compared with a Regional Climate Model (RCM) product obtained from Coordinated Regional Climate Downscaling Experiment (CORDEX). The potential of downscaling the extreme events is assessed considering Bhadra basin in India as the study area through different models (SDSM, TVDM and RCM) during historical period (calibration: 1951–2005, testing: 2006–2012). Next, the changes in precipitation extremes during future period (2006–2035) have been assessed with respect to the observed baseline period (1971–2000), for different Representative Concentration Pathway (RCP) scenarios. All the models indicate an increasing trend in the precipitation, for the monsoon months and maximum increase is noticed using RCP8.5. The annual precipitation during the future period (RCP8.5) is likely to increase by 7.6% (TVDM) and 4.2% (SDSM) in the study basin. An increase in magnitude and number of extreme events during the future period is also noticed. Such events are expected to be doubled in number in the first quarter of the year (January–March). Moreover, the time-invariant relationship (in SDSM) between causal-target variables is needed to be switched with time-varying (TVDM). This study proves that the time-varying property in TVDM is more beneficial since its performance is better than SDSM and RCM outputs in identifying the extreme events during model calibration and testing periods. Thus, the TVDM is a better tool for assessing the extreme events.

     

黄河流域下垫面变化对径流量影响的讨论

20世纪90年代以来,黄河流域径流量连续偏小,目前人们对于偏小的主要原因认识不一。经过对河源地区降水量与径流量关系分析,以及对中游地区渭河、伊洛河、沁河2003年汛期径流量和汛期多年径流量的对比分析认为,径流量偏小应与降水量连续偏小、超过一定量级的暴雨次数偏少、气温的增高以及蒸发量增大等多种因素有关。这些气象因素的变化,主要受气候波动的影响,至于河源区下垫面的破坏、中游中小型水利水保工程等不应是黄河径流量变小的主要原因,因此对未来径流量不需要进行降水量与径流量关系的“一致性处理”。